Jenny List writes about how an undocumented feature in certain ESP32 chips allows the raw I/Q stream to be tapped before the WiFi modem, effectively turning them into software-defined radio receivers. Discovered independently by Espargos and a Reddit user, the mode supports both 2.4 and 5 GHz bands but is limited to receive-only operation.
- Only works on ESP32 variants with earlier Tensilica hardware; Bluetooth-only and non-radio P4 chips won't work
- Transmit capability appears possible but remains undocumented, with the discoverer refusing to share due to "rule 3"
- The 80 Msps 32-bit/sample data rate creates bandwidth challenges for external transfer via SDIO or UART interfaces
- Only works on ESP32 variants with earlier Tensilica hardware; Bluetooth-only and non-radio P4 chips won't work
- Transmit capability appears possible but remains undocumented, with the discoverer refusing to share due to "rule 3"
- The 80 Msps 32-bit/sample data rate creates bandwidth challenges for external transfer via SDIO or UART interfaces
Clef is a 27B multimodal model developed by Cloudflare that transforms state data and schemas of typed questions into structured decisions. By accepting text, JSON, images, or video as input, it returns a probability for every allowed option of each question in a single forward pass, entirely eliminating free-form text generation and output parsing. The model is post-trained from Qwen/Qwen3.8-27B and features a joint schema head that routes evidence to each question and scores all options simultaneously. It is fully compatible with Jev and SystemOne APIs, making it well-suited for deterministic, structured decision-making tasks.
- Supports `choice`, `score`, and `noul` (true/false) question types
- A smaller, faster variant called Clef-Flash is also available
- Achieves strong benchmark results, particularly on BFCL (98.5%), ToolRet (69.2), and API-Bank (91.9%)
- Significantly faster than comparable models, with a median latency of 209.3 ms
- Released under the Apache-2.0 license
- Supports `choice`, `score`, and `noul` (true/false) question types
- A smaller, faster variant called Clef-Flash is also available
- Achieves strong benchmark results, particularly on BFCL (98.5%), ToolRet (69.2), and API-Bank (91.9%)
- Significantly faster than comparable models, with a median latency of 209.3 ms
- Released under the Apache-2.0 license
Shapeshift is a Next.js + React 19 component that turns a single text input into context-aware UI cards. As you type, the box morphs into event cards, checklists, timers, color pickers, bill splitters, converters, polls, and more based on detected intent. Intent classification is powered by TypeSafe Jev, which answers 14 typed questions in a single parallel call, while all value extraction (dates, amounts, units, math) is handled by deterministic code. The project works fully offline by default using a built-in keyword classifier and can optionally use the online Jev model with an API key.
- One Jev call answers 14 typed questions in parallel (speculative fan-out), covering card type plus signals like "is it a video call?" and "is it urgent?"
- A state machine with hysteresis prevents flickering: a card only changes when a challenger wins twice in a row or is very confident
- 19 card types supported, including trip planner, time zone converter, dice roller, countdown, and goal tracker
- Built with TypeScript (strict), Tailwind CSS v4, shadcn/ui, Motion, chrono-node, and zod
- Live demo at shapeshiftui.vercel.app
- One Jev call answers 14 typed questions in parallel (speculative fan-out), covering card type plus signals like "is it a video call?" and "is it urgent?"
- A state machine with hysteresis prevents flickering: a card only changes when a challenger wins twice in a row or is very confident
- 19 card types supported, including trip planner, time zone converter, dice roller, countdown, and goal tracker
- Built with TypeScript (strict), Tailwind CSS v4, shadcn/ui, Motion, chrono-node, and zod
- Live demo at shapeshiftui.vercel.app
Giorgio Mendoza writes that Makerfabs has released the MaTouch ESP32-S3 7.5-inch Quad-Color E-Ink board, pairing an 800×480 four-color electrophoretic display with an ESP32-S3R8 controller, a four-microphone array, a six-axis IMU, and microSD storage for low-power displays and voice-controlled interfaces.
- Priced at $59.80, with an optional OV3660 3-megapixel camera adding $4.80
- The E Ink panel uses a JD79665 controller with a full-screen refresh time of about 20 seconds
- Software support includes ESP-IDF 5.4.2 and Arduino, with published examples for camera capture and voice-activated image browsing
- The board supports 2.4GHz Wi-Fi and Bluetooth 5 LE, with 8MB PSRAM and 16MB SPI flash
- Priced at $59.80, with an optional OV3660 3-megapixel camera adding $4.80
- The E Ink panel uses a JD79665 controller with a full-screen refresh time of about 20 seconds
- Software support includes ESP-IDF 5.4.2 and Arduino, with published examples for camera capture and voice-activated image browsing
- The board supports 2.4GHz Wi-Fi and Bluetooth 5 LE, with 8MB PSRAM and 16MB SPI flash
Thomas Claburn writes that the Pi coding agent hit its 1.0 milestone with a notable reversal on Model Context Protocol (MCP) support, which its creator Mario Zechner previously dismissed as unnecessary. Earendil, the company that acquired Pi in April 2026, attributed the about-face to improvements in MCP and the developers' own changes that made integrating other capabilities easier. The release also introduced Pi Durable, a separate component for orchestrating long-running agentic applications that was split out to preserve Pi's minimalist design.
- Earendil was formed by Armin Ronacher and Colin Daymond Hanna.
- The MCP changes also enable easier use of the Jev decision model within Pi.
- Pi is described as the Flask of agent harnesses (minimal and extensible), contrasted with Django.
- New features include Codemode (a sandbox for tool calls), virtual model support, deferred tool loading, and cache warming for Anthropic models.
- Earendil was formed by Armin Ronacher and Colin Daymond Hanna.
- The MCP changes also enable easier use of the Jev decision model within Pi.
- Pi is described as the Flask of agent harnesses (minimal and extensible), contrasted with Django.
- New features include Codemode (a sandbox for tool calls), virtual model support, deferred tool loading, and cache warming for Anthropic models.
Daniel Curtis writes that generative coding agents have shifted the value of shared UI component libraries from reusable code to regeneratable specifications. Organizations should centralize design tokens, machine-readable guidelines, and verification suites rather than shipping component code. Agents can then produce project-specific components on demand, but a curated set of genuinely difficult widgets and an opinionated design system remain essential to prevent the "Sea of Sameness" and ensure accessibility.
- McKinsey's Business Value of Design study found that top-quartile design index performers outpaced peers by 32 points in revenue growth and 56 in shareholder returns.
- A 2026 Tilburg University study confirmed that generative AI produces a statistically significant homogenization effect, particularly on semantically constrained prompts.
- The Figma MCP server is used to generate UI directly from design files and to run screenshot comparison tests against generated code.
- McKinsey's Business Value of Design study found that top-quartile design index performers outpaced peers by 32 points in revenue growth and 56 in shareholder returns.
- A 2026 Tilburg University study confirmed that generative AI produces a statistically significant homogenization effect, particularly on semantically constrained prompts.
- The Figma MCP server is used to generate UI directly from design files and to run screenshot comparison tests against generated code.
Anmol Baranwal writes a comprehensive guide to AG-UI, an open protocol that standardizes how agents communicate with user-facing applications by replacing custom streaming layers with a unified event stream. The protocol connects agentic backends to frontends across any framework and surface, defining 31 event types grouped into 8 categories covering runs, text, tool calls, reasoning, state, activity, subagents, and custom events. It operates alongside MCP (agent-to-tool) and A2A (agent-to-agent) as the user-facing layer, and its 1.0 specification is stable, backwards compatible, and backed by major tech companies.
- Google, Microsoft, Amazon, and Oracle have adopted the protocol
- SDKs for TypeScript, Python, and .NET are generated from a shared JSON Schema, with community SDKs for Go, Ruby, Rust, Dart, Kotlin, Java, and C++
- Transport-agnostic design supports HTTP SSE, WebSockets, and Protobuf binary format
- AG-UI 1.0 adds subagent support, multimodal tool results, human-in-the-loop interrupts, and token usage tracking
- CopilotKit Intelligence uses captured interaction data with Automatic Learning to extract insights and generate Skills that improve agent behavior over time
- Google, Microsoft, Amazon, and Oracle have adopted the protocol
- SDKs for TypeScript, Python, and .NET are generated from a shared JSON Schema, with community SDKs for Go, Ruby, Rust, Dart, Kotlin, Java, and C++
- Transport-agnostic design supports HTTP SSE, WebSockets, and Protobuf binary format
- AG-UI 1.0 adds subagent support, multimodal tool results, human-in-the-loop interrupts, and token usage tracking
- CopilotKit Intelligence uses captured interaction data with Automatic Learning to extract insights and generate Skills that improve agent behavior over time
Richard Gill writes about his personal Pi coding agent setup, which utilizes OpenAI Codex Sol and Astra models at medium and high thinking levels while adhering to Pi's philosophy of simplicity. He relies primarily on `AGENTS.md` files and custom skills rather than complex configuration.
- Commands taking over 30 seconds automatically move to the background to prevent the agent from getting stuck
- The `sub-pi` extension enables spawning new Pi windows and worktrees via tmux
- Slash commands like `/diff` inject command output directly into context without triggering an LLM turn
- Context files and skills traverse parent directories up to `$HOME`
- Commands taking over 30 seconds automatically move to the background to prevent the agent from getting stuck
- The `sub-pi` extension enables spawning new Pi windows and worktrees via tmux
- Slash commands like `/diff` inject command output directly into context without triggering an LLM turn
- Context files and skills traverse parent directories up to `$HOME`
David Nield writes that DoorDash has unveiled its new drone delivery service, DoorDash Air, promising food delivery in under five minutes on average. The six-propeller aircraft will initially be tested in Northern California in partnership with restaurant brands like Chipotle and Popeyes Louisiana Kitchen. This development coincides with growing backlash against Amazon's Prime Air service in Richardson, Texas, where residents are complaining about the constant buzzing of dozens of drones passing overhead each day.
- DoorDash estimates around 80% of customer orders are light enough to be transported by drone.
- The drones will lower their cargo to the ground rather than landing directly.
- Amazon's Prime Air drones in Texas are permitted to fly between 7am and 8pm.
- DoorDash estimates around 80% of customer orders are light enough to be transported by drone.
- The drones will lower their cargo to the ground rather than landing directly.
- Amazon's Prime Air drones in Texas are permitted to fly between 7am and 8pm.
Shalma Wegsman writes that physicists at MIT and Seoul National University have produced the first complete map of a crystal's quantum geometry, a hidden mathematical landscape that dictates how electrons behave. By combining measurements of Berry curvature and the quantum metric on a kagome solid, researchers have revealed a topological "ghost field" that influences electron motion. This new technique, which utilizes light to probe both the energy and velocity of electrons, offers a powerful tool for understanding exotic material properties and may aid in the search for room-temperature superconductors.
- The "quantum geometry" of a material consists of two parts: the Berry curvature (topological property) and the quantum metric (landscape steepness).
- The researchers used a kagome solid, a material with atoms arranged in a six-sided star pattern, for their primary measurement.
- A separate study by Bohm-Jung Yang's group applied the same method to black phosphorus, demonstrating the technique's versatility.
- The "ghost field" or "ghost charges" in topological materials cause electrons to move as if they are interacting with a force that does not physically exist.
- Understanding the quantum metric was recently crucial for explaining an exotic new form of superconductivity in a 2D crystal.
- The "quantum geometry" of a material consists of two parts: the Berry curvature (topological property) and the quantum metric (landscape steepness).
- The researchers used a kagome solid, a material with atoms arranged in a six-sided star pattern, for their primary measurement.
- A separate study by Bohm-Jung Yang's group applied the same method to black phosphorus, demonstrating the technique's versatility.
- The "ghost field" or "ghost charges" in topological materials cause electrons to move as if they are interacting with a force that does not physically exist.
- Understanding the quantum metric was recently crucial for explaining an exotic new form of superconductivity in a 2D crystal.
